29 lines
1.0 KiB
Python
29 lines
1.0 KiB
Python
import pandas as pd
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from tabulate import tabulate
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from engine.configProcessor import generate_config, create_tensor_field
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from engine.mechanismExecutor import simulation
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from engine.utils import flatten
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from ui.config import state_dict, mechanisms, exogenous_states, env_processes, sim_config
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from engine.multiproc import parallelize_simulations
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def main():
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states_list = [state_dict]
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ep = list(exogenous_states.values())
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config = generate_config(state_dict, mechanisms, ep)
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T = sim_config['T']
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N = sim_config['N']
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configs = [config, config]
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# Dimensions: N x r x mechs
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if len(configs) > 1:
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simulations = parallelize_simulations(simulation, states_list, configs, env_processes, T, N)
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else:
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simulations = [simulation(states_list, configs[0], env_processes, T, N)]
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for result in simulations:
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print(tabulate(create_tensor_field(mechanisms, ep), headers='keys', tablefmt='psql'))
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print
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print(tabulate(pd.DataFrame(flatten(result)), headers='keys', tablefmt='psql')) |